Several measures have previously been defined for threat assessment with various warning and overriding algorithms proposed. They monitor the dynamic traffic and vehicle information in real time and assess the current threat level to decide if warnings should be issued to the driver or automatic braking is needed to avoid collisions. Ĭollision avoidance systems (CAS) are an emerging automotive safety technology that assists drivers in avoiding collisions. Its effect on decreasing the severity of a rear-end collision is studied and its reliability is tested using a well-established physics-based robotics simulator, namely Webots. Furthermore, different warning thresholds are proposed by considering the average driver reaction time. maximum acceleration) needs to be applied. ![]() It directly quantifies the threat level of the current dynamic situation before a required evasive action (i.e. It inherits the properties of the Tlsb and, as such, is coherent with the human judgement of urgency and severity of threats. The Tlsa is a novel time-based approach that focuses on the lead vehicle (as opposed to the following vehicle). In particular, a new threat metric, the time-to-last-second-acceleration (Tlsa), for lead vehicles in rear-end collision is proposed and compared with its counterpart, the time-to-last-second-braking (Tlsb). In this paper, we will focus on two time-based measures that assess both front and rear collision threats. Several measures have already been defined for threat assessment and various CWS have been proposed in literature. ![]() It assesses the potential threat level and decides whether a warning should be issued to the driver through auditory and/or visual signals. A CWS monitors the dynamic state of the traffic in realtime by processing information from various proprioceptive and exteroceptive sensors. Collision Warning Systems (CWS) are safety systems designed to warn the driver about an imminent collision.
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